Swedish National Team selections in ice hockey : A retrospective study
Bibliographic record
Abstract
Countries invest a large amount of money in talent development and talent identification. The Swedish ice hockey federation is reorganizing and evaluating the national team selection system. Relative age effect (RAE) refers to a selection bias when relatively older athletes get selected because maturity can be mistaken for talent. This study aimed to examine the selection patterns in the Swedish ice hockey national team and see if there is a relationship between selected players and their birth month. Studies on selections have been conducted in Canadian ice hockey and different leagues, but no one has investigated selections in national team ice hockey. A Quantitative approach was used, to analyze the sample from this retrospective study.The sample contained 384 players that has been selected for the Swedish youth and junior national team once or more from five different cohorts from 1997-2001. The statistical analyses were conducted through 𝑋!test of association, 𝑋! goodness of fit and factorial ANOVA. The significance level was set to £0,05. Cramers V and h2 was used to measure the effect size. The results showed that 78% of selected players got re-selected, and most players were entering the system early. A relationship between players birth distribution and selection for the Swedish youth and junior national team was obtained, more players selected were born in the first half of the year. No significant difference in birth distribution was found among the players that played in the World Junior Championship (WJC) in 2017-2021. 92 players were selected for the world junior championship (WJC) rosters. 139 spots were available and 58 of these were taken by underaged players. Underaged players showed a significant difference in birth distribution. Underaged players born in the first half of the year were more likely to be selected as underaged for the U20 WJC rosters compared to their relatively younger peers. No significant difference was found in players height and weight between the four birth quarters. In conclusion, the Swedish ice hockey national team has adopted a collectivistic approach, players could enter the system at a later stage and still be selected to play in the U20 WJC. Most players are initially selected at age 16, which can indicate that the system is closed. Differences in players birth distribution were found and players born early in the year are more likely to be selected for the national team, however in the WJC squads the birth distribution evens out.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".